Seismic Risk Model for the Beijing-Tianjin-Hebei Region, China: Considering Epistemic Uncertainty from the Seismic Hazard Models

Jian Ma; Katsuichiro Goda; Kai Liu; Silva Vitor; Anirudh Rao; Ming Wang

doi:10.1007/s13753-024-00568-4

Volume 15 Issue 3

Jun. 2024

Turn off MathJax

Article Contents

Article Navigation > International Journal of Disaster Risk Science > 2024 > 15(3): 434-452

Jian Ma, Katsuichiro Goda, Kai Liu, Silva Vitor, Anirudh Rao, Ming Wang. Seismic Risk Model for the Beijing-Tianjin-Hebei Region, China: Considering Epistemic Uncertainty from the Seismic Hazard Models[J]. International Journal of Disaster Risk Science, 2024, 15(3): 434-452. doi: 10.1007/s13753-024-00568-4

Citation:

Jian Ma, Katsuichiro Goda, Kai Liu, Silva Vitor, Anirudh Rao, Ming Wang. Seismic Risk Model for the Beijing-Tianjin-Hebei Region, China: Considering Epistemic Uncertainty from the Seismic Hazard Models[J]. International Journal of Disaster Risk Science, 2024, 15(3): 434-452. doi: 10.1007/s13753-024-00568-4

Citation:

Jian Ma, Katsuichiro Goda, Kai Liu, Silva Vitor, Anirudh Rao, Ming Wang. Seismic Risk Model for the Beijing-Tianjin-Hebei Region, China: Considering Epistemic Uncertainty from the Seismic Hazard Models[J]. International Journal of Disaster Risk Science, 2024, 15(3): 434-452. doi: 10.1007/s13753-024-00568-4

PDF

Seismic Risk Model for the Beijing-Tianjin-Hebei Region, China: Considering Epistemic Uncertainty from the Seismic Hazard Models

doi: 10.1007/s13753-024-00568-4

1. Key Laboratory of Earthquake Engineering and Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration;
Key Laboratory of Earthquake Disaster Mitigation, Ministry of Emergency Management, Harbin, 150080, China;
2. School of National Safety and Emergency Management, Beijing Normal University, Beijing, 100875, China;
3. Department of Earth Sciences, Western University, London, N6A 5B7, Canada;
4. Global Earthquake Model Foundation, 27100, Pavia, Italy;
5. Shenzhen Key Laboratory of Urban Disasters Digital Twin, Shenzhen, 518023, China

Funds:

and Shenzhen Science and Technology Program (ZDSYS20210929115800001) are gratefully acknowledged.

National Key R&D Program of China (2022YFC3004404)

The financial support received from the Scientific Research Fund of Institute of Engineering Mechanics, China Earthquake Administration (Grant No. 2023B09)

Accepted Date: 2024-05-27

Available Online: 2024-10-26

Publish Date: 2024-06-19

Abstract

Abstract

This study presents a probabilistic seismic risk model for the Beijing-Tianjin-Hebei region in China. The model comprises a township-level residential building exposure model, a vulnerability model derived from the Chinese building taxonomy, and a regional probabilistic seismic hazard model. The three components are integrated by a stochastic event-based method of the OpenQuake engine to assess the regional seismic risk in terms of average annual loss and exceedance probability curve at the city, province, and regional levels. The novelty and uniqueness of this study are that a probabilistic seismic risk model for the Beijing-Tianjin-Hebei region in China is developed by considering the impact of site conditions and epistemic uncertainty from the seismic hazard model.
- Beijing-Tianjin-Hebei region,
- Epistemic uncertainty,
- Seismic risk assessment,
- Seismic risk model

FullText(HTML)

References(65)

References

[1]	Abrahamson, N.A., W.J. Silva, and R. Kamai. 2014. Summary of the ASK14 ground motion relation for active crustal regions. Earthquake Spectra 30: 1025-1055.
[2]	Allen, T.I., and D.J. Wald. 2009. On the use of high-resolution topographic data as a proxy for seismic site conditions (VS 30). Bulletin of the Seismological Society of America 99: 935-943.
[3]	Amendola, C., and D. Pitilakis. 2023. Urban scale risk assessment including SSI and site amplification. Bulletin of Earthquake Engineering 21: 1821-1846.
[4]	Atkinson, G.M., and J. Adams. 2013. Ground motion prediction equations for application to the 2015 Canadian national seismic hazard maps. Canadian Journal of Civil Engineering 40: 988-998.
[5]	Avital, M., R. Kamai, M. Davis, and O. Dor. 2018. The effect of alternative seismotectonic models on PSHA results-A sensitivity study for two sites in Israel. Natural Hazards and Earth System Sciences 18: 499-514.
[6]	Baker, J., B. Bradley, and P. Stafford. 2021. Seismic hazard and risk analysis. Cambridge, UK: Cambridge University Press.
[7]	Bommer, J.J., J. Douglas, F. Scherbaum, F. Cotton, H. Bungum, and D. Fah. 2010. On the selection of ground-motion prediction equations for seismic hazard analysis. Seismological Research Letters 81(5): 783-793.
[8]	Bommer, J., R. Spence, M. Erdik, S. Tabuchi, N. Aydinoglu, E. Booth, D. del Re, and O. Peterken. 2002. Development of an earthquake loss model for Turkish catastrophe insurance. Journal of Seismology 6: 431-446.
[9]	Boore, D. 2004. Estimating Vs(30) (or NEHRP site classes) from shallow velocity models (depths < 30 m). Bulletin of the Seismological Society of America 94(2): 591-597.
[10]	Boore, D.M., J.P. Stewart, E. Seyhan, and G.M. Atkinson. 2014. NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes. Earthquake Spectra 30: 1057-1085.
[11]	Borcherdt, R.D. 1994. Estimates of site-dependent response spectra for design (methodology and justification). Earthquake Spectra 10(4): 617-653.
[12]	Bradley, B.A. 2012. A ground motion selection algorithm based on the generalized conditional intensity measure approach. Soil Dynamics and Earthquake Engineering 40: 48-61.
[13]	BSSC (Building Seismic Safety Council). 2004. NEHRP recommended provisions for seismic regulations for new buildings and other structures, Part 1: Provisions (FEMA 450-1/2003 edition). Washington, DC: Building Seismic Safety Council.
[14]	Calvi, G.M., R. Pinho, G. Magenes, J.J. Bommer, L.F. Restrepo-Vélez, and H. Crowley. 2006. Development of seismic vulnerability assessment methodologies over the past 30 years. ISET Journal of Earthquake Technology 43(3): 75-104.
[15]	Campbell, K.W., and Y. Bozorgnia. 2014. NGA-West2 ground motion model for the average horizontal components of PGA, PGV, and 5% damped linear acceleration response spectra. Earthquake Spectra 30: 1087-1114.
[16]	Chen, H. 2013. General development and design of HAZ-China Earthquake Disaster Loss Estimation System. Recent Developments in World Seismology 2013(3): 45-47 (in Chinese).
[17]	Chen, X., X. Lin, L. Zhang, and K.A. Skalomenos. 2022. Method for rapidly generating urban damage scenarios under non-uniform ground motion input based on matching algorithms and time history analyses. Soil Dynamics and Earthquake Engineering 152: Article 107055.
[18]	Cheng, J., Y. Rong, H. Magistrale, G. Chen, and X. Xu. 2017. An Mw-based historical earthquake catalog for mainland China. Bulletin of the Seismological Society of America 107: 2490-2500.
[19]	Chiou, B.S.J., and R.R. Youngs. 2014. Update of the Chiou and Youngs NGA model for the average horizontal component of peak ground motion and response spectra. Earthquake Spectra 30: 1117-1153.
[20]	Cornell, C.A. 1968. Engineering seismic risk analysis. Bulletin of the Seismological Society of America 58(5): 1583-1606.
[21]	Crowley, H., J.J. Bommer, R. Pinho, and J. Bird. 2005. The impact of epistemic uncertainty on an earthquake loss model. Earthquake Engineering Structural Dynamics 34(14): 1653-1685.
[22]	Crowley, H., V. Despotaki, D. Rodrigues, V. Silva, D. Toma-Danila, E. Riga, A. Karatzetzou, and S. Fotopoulou. 2020. Exposure model for European seismic risk assessment. Earthquake Spectra 36: 252-273.
[23]	D’Ayala, D., and E. Speranza. 2003. Definition of collapse mechanisms and seismic vulnerability of historic masonry buildings. Earthquake Spectra 19: 479-509.
[24]	Danciu, L., Ö. Kale, and S. Akkar. 2018. The 2014 earthquake model of the Middle East: Ground motion model and uncertainties. Bulletin of Earthquake Engineering 16: 3497-3533.
[25]	Dangkua, D.T., Y. Rong, and H. Magistrale. 2018. Evaluation of NGA-West2 and Chinese ground-motion prediction equations for developing seismic hazard maps of mainland China. Bulletin of the Seismological Society of America 108: 2422-2443.
[26]	Dong, W. 2002. Engineering models for catastrophe risk and their application to insurance. Earthquake Engineering and Engineering Vibration 1(1): 145-151.
[27]	Friedman, D.G. 1972. Insurance and the natural hazards. ASTIN Bulletin: The Journal of the IAA 7(1): 4-58.
[28]	Friedman, D.G. 1984. Natural hazard risk assessment for an insurance program. Geneva Papers on Risk and Insurance 9(30): 57-128.
[29]	Gao, M., X. Li, and X. Xu. 2015. GB18306-2015: Introduction to the seismic hazard map of China. Beijing, China: Standards Press of China (in Chinese).
[30]	Grossi, P., H. Kunreuther, and D. Windeler. 2005. An introduction to catastrophe models and insurance. In Catastrophe modeling: A new approach to managing risk, ed. P. Grossi, and H. Kunreuther, 23-42. New York: Springer.
[31]	Grossi, P., D.D. Re, Z. Wang, and K. Lao. 2006. The 1976 Great Tangshan Earthquake: 30-year retrospective. Plymouth, MN: RMS Inc.
[32]	He, C., Q. Huang, Y. Dou, W. Tu, and J. Liu. 2017. The population in China’s earthquake-prone areas has increased by over 32 million along with rapid urbanization. Environmental Research Letters 12: Article 039501.
[33]	Hong, H.P., and C. Feng. 2019. On the ground-motion models for Chinese seismic hazard mapping. Bulletin of the Seismological Society of America 109: 2106-2124.
[34]	Iwahashi, J., and R.J. Pike. 2007. Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature. Geomorphology 86: 409-440.
[35]	Jalayer, F., R. De Risi, and G. Manfredi. 2015. Bayesian cloud analysis: Efficient structural fragility assessment using linear regression. Bulletin of Earthquake Engineering 13: 1183-1203.
[36]	Jiang, J., and F. Hong. 1985. Seismic reliability analysis of multi-story brick building. Earthquake Engineering and Engineering Vibration No. 4: 13-28 (in Chinese).
[37]	Joyner, W.B., and D.M. Boore. 1988. Measurement, characterization, and prediction of strong ground motion. In Earthquake engineering and soil dynamics II: Recent advances in ground-motion evaluation. Proceedings of the American Society of Civil Engineers Geotechnical Engineering Division Specialty Conference, 27-30 June 1988, Park City, UT, USA, 27-30.
[38]	Lemoine, A., J. Douglas, and F. Cotton. 2012. Testing the applicability of correlation between topographic slope and VS30 for Europe. Bulletin of Seismological Society of America 102: 2585-2599.
[39]	Ma, J. 2022. Research on the regional probabilistic seismic risk model development and sensitivity analysis. Ph.D. dissertation. Beijing: Beijing Normal University (in Chinese).
[40]	Ma, J., A. Rao, V. Silva, K. Liu, and M. Wang. 2021. A township-level exposure model of residential buildings for mainland China. Natural Hazards 108: 389-423.
[41]	Martins, L., and V. Silva. 2021. Development of a fragility and vulnerability model for global seismic risk analyses. Bulletin of Earthquake Engineering 19: 6719-6745.
[42]	Massa, M., S. Barani, and S. Lovati. 2014. Overview of topographic effects based on experimental observations: Meaning, causes and possible interpretations. Geophysical Journal International 197(3): 1537-1550.
[43]	McGuire, R.K. 1995. Probabilistic seismic hazard analysis and design earthquakes: Closing the loop. Bulletin of the Seismological Society of America 85(5): 1275-1284.
[44]	McKenna, F. 2011. OpenSees: A framework for earthquake engineering simulation. Computing in Science and Engineering 13: 58-66.
[45]	Mitchell-Wallace, K., M. Jones, J. Hillier, and M. Foote. 2017. Natural catastrophe risk management and modelling: A practitioner’s guide. Hoboken, NJ: John Wiley & Sons.
[46]	Musson, R.M.W. 1999. Determination of design earthquakes in seismic hazard analysis through Monte Carlo simulation. Journal of Earthquake Engineering 3(4): 463-474.
[47]	Pagani, M., D. Monelli, G. Weatherill, L. Danciu, H. Crowley, V. Silva, P. Henshaw, and L. Butler et al. 2014. OpenQuake engine: An open hazard and risk software for the global earthquake model. Seismological Research Letters 85(3): 692-702.
[48]	Rossetto, T., I. Ioannou, and D.N. Grant. 2015. Existing empirical fragility and vulnerability functions: Compendium and guide for selection. GEM Technical Report 2015-1. Pavia, Italy: GEM Foundation.
[49]	Silva, V., D. Amo-Oduro, A. Calderon, C. Costa, J. Dabbeek, V. Despotaki, and M. Pittore. 2020. Development of a global seismic risk model. Earthquake Spectra 36(S1): 372-394.
[50]	Silva, V., H. Crowley, M. Pagani, D. Monelli, and R. Pinho. 2014. Development of the OpenQuake engine, the Global Earthquake Model’s open-source software for seismic risk assessment. Natural Hazards 72: 1409-1427.
[51]	Strasser, F.O., J.J. Bommer, K.A.R.İN. Şeşetyan, M. Erdik, Z. Çağnan, J. Irizarry, X. Goula, and A. Lucantoni et al. 2008. A comparative study of European earthquake loss estimation tools for a scenario in Istanbul. Journal of Earthquake Engineering 12(S2): 246-256.
[52]	Villar-Vega, M., V. Silva, H. Crowley, C. Yepes, N. Tarque, A.B. Acevedo, M.A. Hub, and C.D. Gustavo et al. 2017. Development of a fragility model for the residential building stock in South America. Earthquake Spectra 33: 581-604.
[53]	Wald, D.J., and T.I. Allen. 2007. Topographic slope as a proxy for seismic site conditions and amplification. Bulletin of the Seismological Society of America 97: 1379-1395.
[54]	Wieland, M., M. Pittore, S. Parolai, J. Zschau, B. Moldobekov, and U. Begaliev. 2012. Estimating building inventory for rapid seismic vulnerability assessment: Towards an integrated approach based on multi-source imaging. Soil Dynamics and Earthquake Engineering 36: 70-83.
[55]	Woessner, J., D. Laurentiu, D. Giardini, H. Crowley, F. Cotton, G. Grünthal, G. Valensise, and R. Arvidsson et al. 2015. The 2013 European Seismic Hazard Model: Key components and results. Bulletin of Earthquake Engineering 13: 3553-3596.
[56]	Wu, J., C. Wang, X. He, X. Wang, and N. Li. 2017. Spatiotemporal changes in both asset value and GDP associated with seismic exposure in China in the context of rapid economic growth from 1990 to 2010. Environmental Research Letters 12(3): Article 034002.
[57]	Xie, Z., Y. Lv, Y. Fang, and B. Shi. 2017. Relocated seismicity and its relation with active faults in Beijing-Tianjin-Hebei area. Earthquake 37(3): 72-83 (in Chinese).
[58]	Xiong, C., X. Lu, J. Huang, and H. Guan. 2019. Multi-LOD seismic-damage simulation of urban buildings and case study in Beijing CBD. Bulletin of Earthquake Engineering 17: 2037-2057.
[59]	Yepes-Estrada, C., V. Silva, J. Valcárcel, A.B. Acevedo, N. Tarque, M.A. Hube, G. Coronel, and H.S. María. 2017. Modeling the residential building inventory in South America for seismic risk assessment. Earthquake Spectra 33: 299-322.
[60]	Yin, Z. 1994. A dynamic model for predicting earthquake disaster losses. Journal of Natural Disasters 3(2): 72-80 (in Chinese).
[61]	Yu, X., and D. Lu. 2016. Probabilistic seismic demand analysis and seismic fragility analysis based on a cloud-stripe method. Engineering Mechanics 33: 68-76 (in Chinese).
[62]	Yu, Y.X., S.Y. Li, and L. Xiao. 2013. Development of ground motion attenuation relations for the new seismic hazard map of China. Technology for Earthquake Disaster Prevention 8(1): 24-33 (in Chinese).
[63]	Zhang, L., J. Jiang, and J. Liu. 2002. Seismic vulnerability analysis of multistory dwelling brick buildings. Earthquake Engineering and Engineering Vibration 22: 49-55 (in Chinese).
[64]	Zhang, Y., Y. Ren, R. Wen, H. Wang, and K. Ji. 2023. Regional terrain-based VS 30 prediction models for China. Earth, Planets and Space 75(1): Article 72.
[65]	Zhang, Y., S. Zheng, L. Sun, L. Long, and L. Li. 2021. Developing GIS-based earthquake loss model: A case study of Baqiao District, China. Bulletin of Earthquake Engineering 19: 2045-2079.